PY 211 EXAM 1

Statistics

Way to organize, interpret, and communicate information

Variable

Characteristic that can have different values

Value

Possible number or category that a score can have

Score

A particular person’s value on a variable

Independent Variable

the variable that is manipulated

Dependent Variable

the variable being observed and measured

Numeric Variable

Quantitative

Values are numbers

Nominal Variable

Qualitative 

Values are categories

Names rather than numbers

Discrete

variables have specific values and cannot have values between these specific values

Continuous

variables can, in theory, have an infinite number of values between any two values

Ordinal

Values correspond to relative position of things measured

Distances among levels is unknown and may not be equal

Equal Interval

Differences among values correspond to differences in underlying thing being measured

No such thing as 0 for interval

Ratio

Same as interval (equal spacing), but now there’s a true zero

Zero means nothing at all

Population

who you are studying

Sample

small subset of the population being studied

Simple Random Sampling

everyone in the population has the same chance of being chosen for the sample

Stratified Sampling

Identify different “strata” or groups, sample from these groups proportional to their size in the population

Convenience Sampling

Using an easily accessible population

Experimental Design

Use random assignment

Manipulate independent variable

Quasi-Experimental Design

Manipulate independent variable, but no random assignment.

Non-experimental Design

No manipulation

Observe variables as they naturally occur

Find relationships

Descriptive Statistics

Summarize/organize scores from a research study

Inferential Statistics

Draw conclusions/make inferences that go beyond the scores from a research study

Operational Definition

A process by which a psychologist defines something in terms of the operations (procedures, actions, or processes)

Central Tendency

Most representative value of a group of scores

Mode

Most frequently occurring number in a distribution

Median

Middle score when all scores are arranged from lowest to highest

Mean

Sum of all the scores divided by the number of scores

Amodal

no repeated value in the dataset, there is no mode

Variability

refers to differences among the scores of participants

1.Range

2.Sum of Squares (SS)

3.Variance (SD²)

4.Standard deviation (SD)

Range

Difference between highest and lowest score

Deviation Score

Degree of “atypicalness” of a score

Always equal zero

Score - Mean = ?

Sum of Squares (SS)

Deviation Scores Squared

Larger means more variance

Variance

The average of each score’s squared difference from the mean

1.Subtract the mean from each score

2.Square each of these deviation scores

3.Add up the squared deviation scores

4.Divide the sum of squared deviation by the number of scores

Standard Deviation

Approximately the average amount that scores in a distribution vary from the mean

Square Root of the variance

Z Scores

represent the number of standard deviations a score is above or below the mean

Normal Distribution

Most common type of distribution

Probability

Likelihood an something will happen given the current conditions

Sampling Error

a certain degree of error in the measurement since the sample is not perfect

Hypothesis

A prediction intended to be tested in a research study

Must be specific enough to test

Theory

A set of principles that attempt to explain various phenomena

Null Hypothesis

The assumption that there is no real effect, no difference, or no relationship between things you are measuring, and that any observed results are merely doto chance

Hypothesis Testing Process

1. Restate the question as a research hypothesis and null

2. Determine the characteristics of the comparison distribution.

3. Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected.

4. Determine your sample’s score on the comparison distribution.

5. Decide whether to reject the null hypothesis.

Directional (one-tailed) hypothesis

Direction of the result is predicted

Non- Directional (two-tailed) hypothesis

Direction of the result is not predicted

P-value

probability of obtaining a result equal to or more extreme than what was actually observed, assuming that the null hypothesis is true

compared to a significance level of 0.05

Burden of Proof

When we reject the null hypothesis, all we are saying is that our results support the research (or alternative) hypothesis

When we fail to reject the null hypothesis, all we are saying is that the results are inconclusive